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Quantitative Vulnerability Assessment for Economic Systems

Vulnerability and the Process of Recovery for Households and Companies in Phang-Nga and Phuket Provinces in Thailand

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Philipp Willroth

In 2004 tsunami waves caused huge economic losses along the coastline of Southern Thailand. These resulted from direct damages and the following economic downturn. This study investigates the factors that led to this vulnerable situation. One of the greatest challenges in vulnerability research is the quantification. To answer this question, a wide database has been used, encompassing highly accurate remote sensing data, quantitative surveys and qualitative focus group discussion data. These data have been integrated in a structural equation model to reproduce factors and relations leading to the hazard induced effects and the capabilities to cope with. The model showed that the impact was almost completely compensated for by households’ and companies’ internal and external resilience capabilities.

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9 Application of vulnerability model on the meso-level for the post-tsunami situation

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9.1 Household vulnerability on the community level In order to compare the study communities, the households’ structural equa- tion model has been adapted to all interviewed households in order to predict their vulnerability for their current situation using the reference scenario of the tsunami 2004 in terms of physical impact and the external help situation. Both input and output data for the structural equation model are z-transformed values, and therefore interpretations are only possible in relation to the study communi- ties and in terms of significances of the mean values. Comparing the four study villages to each other, it can be seen that the households in Ban Nam Khem recovered significantly more slowly than house- holds in the other three study areas, in terms of both the physical rehabilitation to the pre-tsunami level and the recovery of household income. The significance test reveals that Ban Nam Khem shows the strongest restrictions in its recovery potential. The other three communities can be split up into two separate recov- ery groups: on the one hand, there is the community of Thai Muang, which was only slightly directly affected but severely indirectly affected, and shows similar recovery values to the municipality of Patong Beach, both in terms of direct and indirect recovery. On the other hand, there is the strongly affected community of Khao Lak, which can be placed between the slowly recovering community of Ban Nam Khem and the rapidly recovering communities of Thai Muang and Patong Beach (cp. Table 66). 208...

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